AutoStore™, the global leader in intelligent fulfillment, announces the CubeVerse platform and new AI-driven capabilities, marking a major step toward self-optimizing fulfillment. AutoStore is introducing new cloud software, AI-powered analytics, and robotic workflows for order preparation and system optimization that can deliver higher throughput in existing systems without additional hardware.
After more than two decades of pioneering cube storage automation, AutoStore is now moving beyond automation alone toward intelligent fulfillment systems that continuously sense, decide, and improve in real time. The announcement reflects a shift in the market from asset-centric automation to decision-centric fulfillment, as companies look to connect machines, software, data, and people into more intelligent, coordinated operations. With CubeVerse and AutoStore Intelligence, AutoStore enables better, faster decisions across design, deployment, operations, and optimization-working alongside existing WMS and WES solutions rather than replacing them.
For customers, this means unlocking hidden capacity in existing systems, simplifying operations, and accelerating the path to fully autonomous fulfillment, powered by learnings continuously drawn from AutoStore’s global community of thousands of live systems, enabling improvements that compound across the installed base.
“Fulfillment is becoming a real-time, intelligence-driven discipline. If systems can’t sense, decide, and adapt continuously, everything upstream breaks,” said Parth Joshi, Chief Product Officer at AutoStore. “With the launch of the CubeVerse platform and our AI-driven capabilities, we’re bringing intelligence across the entire lifecycle—from design to daily operations to advanced analytics to optimizations. This is a major first step in our AI strategy and reinforces our focus on innovation as the market leader in automated fulfillment.”
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The Spring 2026 product announcement introduces a new CubeVerse cloud platform, designed to unify data, applications, and AI capabilities across the fulfillment lifecycle, alongside AI-powered software and analytics, and expanded automation capabilities. Together, these capabilities lower total cost of ownership, improve performance and predictability, reduce operational complexity, and support longer operating hours, including full 24/7 operation.
After a decade of rapid investment in warehouse automation, the industry is facing a new challenge: seventy-five percent of companies say synchronizing their supply chain is difficult as logistics networks grow more complex. The question is no longer just how to automate, but how to coordinate machines, software, data, and people into systems that make better decisions and run reliably around the clock.
CubeVerse and AutoStore Intelligence provide the data, simulation, and analytics capabilities that enable this shift—helping customers orchestrate fulfillment decisions across the system lifecycle without replacing existing orchestration or control layers.
The Spring 2026 Product Portfolio
Built on the CubeVerse platform, this Spring’s announcements span the fulfillment lifecycle—from system design and AI-driven optimization to autonomous order preparation.
CubeVerse™ Platform
CubeVerse provides a single platform to design, deploy, and run AutoStore systems. It spans the full system lifecycle—from design and simulation to deployment, operations, analytics, and optimization. CubeVerse simplifies integrations, keeps operations consistent across sites, and helps customers avoid overbuilding and keep costs under control.
AutoStore Intelligence
AutoStore Intelligence applies built-in AI to real operational data across the platform to orchestrate fulfillment in real time. It optimizes robot movement through CubeControl, reduces congestion, and clears traffic bottlenecks to deliver higher throughput during peak periods, with performance continuously improving over time, without requiring additional robots or grid expansion. Embedded across CubeVerse, AutoStore Intelligence uses 20+ proprietary models to predict issues, optimize operations, and deliver measurable performance improvements across the automation lifecycle.
SOURCE: Buisnesswire























